Application of decision trees in the identification of fraudulent websites

• Autores: Layme Fernández, Christian, Suri Canaza, José Manuel, Peña Ugarte, David Jose, Luna Quispe, Jhon Yoset
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/49
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/49; https://doi.org/10.48168/innosoft.s8.a49; https://purl.org/42411/s8/a49; https://n2t.net/ark:/42411/s8/a49
• Nivel de acceso: acceso abierto
• Materia: Decision Tree; Python; Computer Security; Web Sites; Árbol de Decisión; Seguridad Informática

Computer security is a very important area in any system that has an internet connection because there are fraudulent websites that can carry out criminal actions towards a person, organization or other entity. Therefore, it is necessary to be able to detect which websites are fraudulent before being able to enter them, for this an implementation was developed through Decision Trees with the Python language to detect and classify them as Legitimate, Suspicious and Fraudulent through 1353 cases that they rank websites.